Optimal operating conditions analysis for a multi-effect distillation plant according to energetic and exergetic criteria.

被引:30
作者
Carballo, Jose A. [1 ,3 ]
Bonilla, Javier [2 ,3 ]
Roca, Lidia [2 ,3 ]
De la Calle, Alberto [4 ]
Palenzuela, Patricia [2 ,3 ]
Alarcon-Padilla, Diego C. [2 ,3 ]
机构
[1] Univ Almeria, Ctra Sacramento S-N, La Canada De San Urbano 04120, Almeria, Spain
[2] CIEMAT Plataforma Solar Almeria, Ctra Senes S-N, Tabernas 04200, Almeria, Spain
[3] UAL PSA CIEMAT Joint Ctr, CIESOL Res Ctr Solar Energy, Almeria, Spain
[4] CSIRO Energy, 10 Murray Dwyer Ct, Mayfield West, NSW 2304, Australia
关键词
Optimization; Multi-criteria; Genetic algorithm; Desalination; Modelica; ABSORPTION HEAT-PUMP; DESALINATION SYSTEMS; THERMOECONOMIC ANALYSIS; WATER DESALINATION; MED-TVC; SOLAR; SEAWATER; PERFORMANCE; SIMULATION; COST;
D O I
10.1016/j.desal.2017.12.013
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
In order to reduce the energy cost while improving the process operation, a study which aims to analyze the influence of the operational parameters variations and determine the optimal operating conditions of a pilot multi-effect desalination system (MED) at CIEMAT-Plataforma Solar de Almeria (PSA) has been performed. An equation-based object-oriented mathematical model of the experimental MED plant, implemented using the modeling language Modelica and previously developed, calibrated and validated, has been adapted to carry out this study. Firstly, an energetic and exergetic analysis of the process under nominal conditions has been carried out, revealing the key sources of energy and exergy consumption. On the one hand, the thermal energy contained in the mass outflows are the main responsible source of the high energy consumption, on the other hand the entropy generation and the heat exchanged with the environment are the responsible of the exergy degradation. Secondly, a study on the influence of the operational parameters shows that the production of the real plant under nominal conditions is far from the maximum simulated values and some operational parameters have not a great influence in the process with respect to the rest. Finally, using a genetic optimization algorithm implemented in the modeling tool, a optimization process taking into account different energy and exergy performance criteria, sets optimal operational set points.
引用
收藏
页码:70 / 76
页数:7
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